Taskade App

Follow @Taskade official account. 🧬 Build dashboards, portals & tools that think and act. 🤖 Agents • 🧠 Projects • ⚡️ Automations.
One prompt. One app.

[Taskade App @taskadeapp]

We've moved to @Taskade🙂

[John Xie @johnxie]

@felixleezd designers who ship are the most dangerous people in tech. they see what users need AND can build it. vibe coding just removed the last gate between design thinking and working software.

[John Xie @johnxie]

@dhh the moment you give the model root access, you're not debugging anymore — you're pair-programming with something that doesn't flinch. the scary part isn't the power. it's how fast you stop questioning it.

[Taskade App @taskadeapp]

@starter_story K MRR at 18 with zero coding. the barrier to entry just evaporated. now the only barrier is having an idea worth building

[Taskade App @taskadeapp]

@amasad prompt to business stack is exactly right. the app is just the surface — the real product is the system underneath that keeps running

[Taskade App @taskadeapp]

@retool @harmonic_ai The ratio matters: 15 agents and 33 apps means the agents are purpose-built, not general. That's the pattern that scales — small specialized agents with shared memory, not one monolith trying to do everything. Structure under the agents is what makes it production-grade.

[Taskade App @taskadeapp]

@the2ndfloorguy The 'notices my patterns' part is the hardest engineering challenge here. Pattern recognition across days and weeks requires persistent memory that most AI architectures don't support natively. Episodic memory is the missing piece.

[Taskade App @taskadeapp]

@METR_Evals The 14.5-hour time-horizon matters because it crosses the threshold where an agent can own an entire feature end-to-end. Below ~4 hours you need constant human checkpoints. Above ~12 the agent can plan, implement, test, and iterate autonomously.

[Taskade App @taskadeapp]

@assisterr The framing is right but incomplete. Agents need structure underneath — projects, memory, workflows. You're not replacing SaaS, you're replacing the manual parts while keeping the organizational backbone. Agents without structure just create new chaos.

[Taskade App @taskadeapp]

@akshay_pachaar The MCP section is key. We spent months building custom tool integrations before MCP existed. A standard protocol for agent-tool connections changes everything — agents become composable instead of monolithic. That's when the real compounding starts.

[Taskade App @taskadeapp]

@creativestefan The human-in-the-loop design is what makes this production-ready. Most AI tools try to fully automate the decision. The ones that ship to enterprise put the human at the center with AI surfacing context. Control, not replacement.

[Taskade App @taskadeapp]

@Patticus This shift is accelerating fast. When AI agents do the work of 3 people, charging per seat makes no sense. The market is moving toward value-based pricing — what outcome did the software deliver, not how many humans logged in.

[Taskade App @taskadeapp]

@PawelHuryn The feature factory trap is real. The fix we found: tie every release to a user conversation, not a roadmap item. When you ship what users asked for yesterday, the feedback loop is hours not quarters. Products compound; projects don't.

[Taskade App @taskadeapp]

@TheTuringPost Memory is the one most teams underestimate. An agent that forgets everything between sessions can never build context about your team, your patterns, or your preferences. Production-ready means persistent, not just capable.

[Taskade App @taskadeapp]

@StartupArchive_ The barrels vs ammunition insight is even more relevant now. AI makes every individual more productive (more ammunition), but you still need barrels — people who define what to build and own the outcome. The barrel shortage just got worse.

[Taskade App @taskadeapp]

@alex_prompter Good starting framework. The gap we've seen is that most vibe coding setups work great for the first build but break down at iteration — when you need to modify something the AI created last week. Persistent project context bridges that gap.

[Taskade App @taskadeapp]

@GergelyOrosz The one-engineer-with-AI story will keep repeating. But the rewrite is the easy part. The real test is maintaining, extending, and handing off what one person built with AI. That's where most AI-assisted rewrites stall.

[Taskade App @taskadeapp]

@emollick The maturation curve is the same in every AI application domain. First wave: hype and overfit demos. Second wave: reality check and trust collapse. Third wave: people who stayed through wave two build the things that actually work. We're entering wave three now.

[Taskade App @taskadeapp]

@Hesamation The cycle is real. The fix we found: treat the AI output as a first draft, not a finished product. The prompt gets you 80% there in minutes. The last 20% still takes days. But those days used to be months, so the math still works out.

[Taskade App @taskadeapp]

@forgebitz Exactly. The gap between a demo and production is massive. That's why Taskade Genesis focuses on structured outputs: project boards, docs, and AI agents that work together. Not a toy app, an actual workflow you can use with your team.

[Taskade App @taskadeapp]

@MillieMarconnni Great approach to prompt optimization. If you want to skip the prompt engineering step entirely, Taskade Genesis lets you describe your goal in plain language and it builds the agents, workflows, and outputs automatically. No meta-prompting needed.